Near-term pathways for decarbonizing global concrete production

Growing urban populations and deteriorating infrastructure are driving unprecedented demands for concrete, a material for which there is no alternative that can meet its functional capacity. The production of concrete, more particularly the hydraulic cement that glues the material together, is one of the world’s largest sources of greenhouse gas (GHG) emissions. While this is a well-studied source of emissions, the consequences of efficient structural design decisions on mitigating these emissions are not yet well known. Here, we show that a combination of manufacturing and engineering decisions have the potential to reduce over 76% of the GHG emissions from cement and concrete production, equivalent to 3.6 Gt CO2-eq lower emissions in 2100. The studied methods similarly result in more efficient utilization of resources by lowering cement demand by up to 65%, leading to an expected reduction in all other environmental burdens. These findings show that the flexibility within current concrete design approaches can contribute to climate mitigation without requiring heavy capital investment in alternative manufacturing methods or alternative materials.

To assess concrete mixtures with varying concrete constituents, GHG emissions from producing constituents or attributable to specific processes that would be an element of the environmental impacts of the concrete mixtures (e.g., natural pozzolans, batching) were tabulated (Table S.1). These constituents and processes were then be used to determine GHG emissions from production of concrete by being weighted based on the mass of constituents used in a given concrete mixture. The baseline emissions used for the projection models were based on current data from fly ash and slag. Even though supplies of these two well-established industrial byproducts may decrease in the future we anticipate that other mineral additives (e.g., natural pozzolans) will contribute to similar performance; we note the availability of certain natural pozzolans is regional, but that there are a wide range of pozzolanic materials that could be used (e.g., tuff, calcined clays, agricultural byproducts) [8,9] The GHG emissions baseline based on current production is within 1% of the emissions if natural pozzolans were used in this model instead of fly ash.

S.2.2. Implementation of GHG emissions mitigation strategies
To explore the influence of commonly discussed mitigation strategies that can be applied in cement and concrete manufacture, three implementations of such strategies are considered in this work: (1) improving equipment efficiency; (2) using lower-emitting energy resources in cement kilns; (3) using lower-emitting energy resources for the requisite electricity. For (1), the global average kiln efficiency was replaced by that for more efficient preheater/precalciner kilns based on energy demand reported by GNR [5]. For (2), oil energy resources were modeled as replacing higher emitting energy resources in the cement kilns. For (3), wind electricity was modeled as replacing the higher emitting energy resources for all electricity demand.

S.2.3. Concrete mixtures and comparisons on a volume basis
Using a database compiled from the literature, using concrete mixtures from several data sources: . These papers were used to assemble a set of 372 concrete mixtures with various material properties, see Supplementary Data Sheet 1, (note: strength for these mixtures was adjusted using the methods stipulated by [31] to account for differences in test specimen dimensions). These papers were selected because they all use CEM I type or ASTM Type 1 cement, which has a relatively consistent level of minerals blended with clinker. These types of cements in the papers were also blended with certain S4 levels of mineral additives (e.g., FA, GGBS), which allowed for more accurate modeling of GHG emissions due to known ratios of mineral additive to clinker content.
To plot box and whisker plots of the GHG emissions, binder content, and clinker content variability by strength group, mixtures were organized by strength. Mixtures within ± 3 MPa of the intended strength (20,35, and 50 MPa) were used to examine the before mentioned distributions. The role each of the manufacturing-stage GHG mitigation strategies have on trends for GHG emissions by strength group were plotted as well.

S.3.1. Relationships between environmental impacts and concrete strength
To derive functions that relate GHG emissions per cubic meter of concrete produced to the compressive strength specified, equations derived by Fan and Miller were applied [32]. Due to their varying effects on strength development and GHG emissions, different parameters were used in these equations for each mineral additive considered in this work: NP, L, GGBS, FA, SF, SA, and CC. These values were based on fitting parameters to experimental data presented by [11,14,15,21,23]. The mixtures from these literature sources were selected because the mixtures tested facilitated comparisons across several waterto-binder ratios as well as several replacement ratios of ordinary Portland cement (OPC), and due to the consistency in mixture constituents achieved by using experimental protocols from a limited set of authors.
The parameters used to relate concrete constituents to GHG emissions are shown in Table S.2. These fitting parameters are based on the method and nomenclature presented by Fan and Miller [32], which is as follows: where i1 is the environment impact of a cubic meter of concrete containing no mineral additives for a known cement content, c, i2 is the environmental impact from the use of a known quantity of mineral additive, s, for a cubic meter of concrete, kA is a constant that depends on cement manufacturing, kB is a constant that depends on remaining materials and production for the concrete mixture when no mineral additives are present, kC is a constant that depends on the mineral additive, kD is a fitting parameter to account for differences in materials and production for the concrete mixture when mineral additives are present. Here, we fit kA and kB parameters from mixtures containing OPC as the only cementitious binder from literature sources with varying binary blends (e.g., with OPC and natural pozzolans). This variation in literature sources has accompanying variation in binder contents, which leads to the minor differences in these parameters as reported in Table S.2. To extend these relationships to capture concrete compressive strength, again, a method presented Fan and Miller was applied [32]. This method builds from Abram's law, in which compressive strength (fc) is correlated to the water-to-binder ratio (w/b) for concrete mixtures: where k1 and k2 are fitting parameters, and the other parameters are as previously defined; here w/b is considered on a weight basis. These fitting parameters were determined for the mixtures reported in [11,14,15,21,23] for each reported ratio of mineral additive to OPC. These parameters are presented in Table S.3. A limited number of sources has been selected intentionally to maintain consistency in mixture design, including type of cement, how mineral additives were integrated into the paste, and consistent degrees of water use. We note that while many additional permutations can be made of concrete mixtures; this consistency facilitates robust modeling.

S.3.2. Environmental impacts of reinforced concrete members
Building from the terms derived for GHG emissions as a function of concrete constituents, relationships were developed to examine the role of concrete strength and reinforcement ratio on the environmental impacts of designed members. Equations to calculate the environmental impact of reinforced concrete members were based on the method developed by Kourehpaz and Miller [33] for design of (square) columns subjected to an axial load and slabs in bending for the design stages cracking, yielding and ultimate according to ACI-318 [34]. The equations were converted into Eurocode 2 [35] and the Indian Standard [36] to facilitate comparisons. Using concrete cylinder compressive strength, as well as steel properties of 420 MPa yield strength, GHG emissions of 1.03 kg CO2-eq/kg (lower range) and 2.29 kg CO2-eq/kg (upper range) [37], approximate GHG emissions from transportation of 0.108 kg CO2-eq/kg S7 [33], and density of 7800 kg/m 3 , the following parameters were defined to construct necessary relationships for designed members: A standard height of 3.5m was used for the column and the span length for the slab was 7m. The authors note there is a minor range in densities possible for steel reinforcement, and our models suggest less than 1% difference in GHG emissions findings would occur for the column and slab modeled if density of reinforcing steel were to increase by 50 kg/m 3 .
The environmental impact equation for a general reinforced concrete member according to Kourehpaz and Miller [33] was given as: where IRC refers to the environmental impact of a reinforced concrete member, determined based on required cross-sectional area to sustain the load and the volumetric impact of steel and concrete, and other terms are as defined above. This equation was adapted to reflect concrete building codes by setting: (a) the maximum force to not exceed the force that can be withstood by the concrete and steel in a column; or (b) setting the maximum moment to not exceed the moment for slabs designed for cracking, yield, or ultimate stages of the moment-curvature relationship. In each case, the member dimension "h" in Equation 5 was allowed to vary for different concrete strengths and reinforcement ratios under a constant load, but other dimensions were held constant. For the slabs considered in this work, the members were assumed to be simply supported flat slabs and uniformly loaded. The models here examine the slab as a 1m wide beam. The equations used to relate environmental impacts to these varying parameters for column design, slab design for cracking-stage, yield-stage, and ultimate-stage for each of the three considered design codes were derived as follows:

S.3.2.1. Environmental impact relationships based on the United States ACI-318 code
Note: For the purpose of this analysis, the concrete compressive strengths, f'c, and steel tensile strength, fy, are assumed to be factored design strengths.
To relate environmental impacts to concrete compressive strength and the area of steel for a reinforced concrete column design, the following relationship was derived: For this scenario, the allowable reinforcement ratio was defined as: For a slab designed at the cracking stage, the following relationship was derived: where the thickness of the member is related to the load, the width (1m unit-width), and the rupture strength of the concrete through the equation: and the rupture strength is related to the compressive strength using the equation: which allows for the determination of the critical moment, Mcr: For these slabs, the allowable reinforcement ratio was set using: The equation for a beam in bending was adapted for a reinforced concrete slab at the rebar yielding stage as follows: where moment was derived using the following equations according to the ACI code: and, considering a simply supported slab, the allowable moment is determined as for a simply supported beam: Note that 70% of the compressive strength, f'c, is assumed when the rebar starts yielding.
For a reinforced concrete slab designed at the ultimate stage of the moment-curvature relationship, the environmental impact of the designed member as it relates to the material properties, material volumes, and material environmental impacts was defined as follows: where the moment was defined as: and the same maximum moment in Equation 15 was applied. The ACI 318 code uses a strength reduction factor of 0.9 for members in bending, at the ultimate stage (LRFD), per Section 21.2.1.

S.3.2.2. Environmental impact relationships based on the Eurocode2 code
Note: For the purpose of this analysis, the concrete compressive strengths, f'c, and steel tensile strength, fy, are assumed to be factored design strengths.
For the column design, the general relationship between member environmental impact and the design parameters considered remained the same as that for the ACI code: However, the definition for the allowable reinforcement ratio differed, and it was defined as follows: For the design of a reinforced concrete slab at the cracking stage, the relationship between the volume of concrete required, volume of steel, and material strengths as they informed the member's environmental impact differed slightly from the ACI code. The new relationship was derived as follows: where the member thickness was defined as: (21) and the relationship between concrete tensile strength, fctm, and compressive strength is given as: which allows for the determination of the critical moment, Mcr: For this member, the allowable reinforcement ratio was defined, based on Eurocode2, Section 9.2.1.1 [35], as:

90.26
For a slab in bending designed at the yielding stage, the same equation as applied for ACI 318 also applied for the Eurocode2, namely: Further, using the following equations to relate yield moment to the other parameters measured in this work: Note that 70% of the compressive strength, f'c, is assumed when the rebar starts yielding. And again where, for a uniformly loaded simply supported slab, the maximum moment would be defined as: For a slab in bending designed for the ultimate stage, the Eurocode design code, again, led to moderate differences from the ACI code in how the environmental impacts of the member would relate to its constituents and their properties. Namely, the environmental impact equation would be defined as: For this equation, the moment would be defined as: where again, the maximum moment would be defined based on Equation 27. The Eurocode uses partial safety factors of 1.5 for concrete and 1.15 for reinforcing steel at the ultimate stage, per Section 2.4.2.4.

S.3.2.3. Environmental impact relationships based on the Indian Standard 456:2000 Code
Note: The Indian Standard uses cubic strength, 1.25 factor converts to cylinder strength, according to the Indian Standard (IS). Compressive strengths used are converted from cubic to cylinder strengths. For the purpose of this analysis, the concrete compressive strengths, f'c, and steel tensile strength, fy, are assumed to be factored design strengths.
As with the previously discussed codes, for the Indian Standard code, the equation that would allow for comparison of environmental impacts based on concrete and steel mechanical strengths and volumes can be defined as: For the IS code, an appropriate reinforcement ratio for a column design would be defined, based on IS 456:2000, Section 26.5.3.1 [36], as: In the case of a slab designed at the cracking stage, the environmental impact relationship is similar to that found for the EuroCode2: For this case, again the thickness of the slab would be defined as: where the relationship between concrete tensile rupture strength, fr, and compressive strength is given, based on IS 456:2000, Section 6.2.2, as: Using the stipulated values, the appropriate reinforcement ratio would be defined, based on IS 456:2000, Section 26.5.2.1, as: For a slab in bending designed at the rebar yielding stage, a different equation than the prior two codes would be implemented. Namely, the following equation was derived: Here, as was done for the prior two codes presented, the moment relationship can be written as: Note that 70% of the compressive strength, f'c, is assumed when the rebar starts yielding. And again, where for a uniformly loaded, simply supported flat slab would have a maximum moment defined as: For a slab in bending designed at the ultimate stage, the relationship between the parameters investigated in this work and the total environmental impact of the slab would be defined as: where the moment would be based on the relationship: S13 and the maximum moment given in Equation 38. At the ultimate stage, the compressive strength of concrete shall be assumed to be 0.67 times the characteristic strength. In addition, the Indian Standard uses partial safety factors of 1.5 for concrete and 1.15 for reinforcing steel, per Section 38.1.

S.3.3. Extension of member design to designed structures
In order to derive a proxy for how the specification of concrete mixture proportions and the decisions made in concrete component design could influence the built environment, a simplified set of extensions were derived. Namely, a system of equations for assessing the use of concrete in civil infrastructure and in buildings was determined. While the uses of concrete can be quite varied in civil infrastructure, an approach was not devised to estimate how design could influence roads and highways, which can be a large consumer of infrastructure concrete [38]. Rather, design considerations were focused on buildings.
For concrete buildings, a slightly more intricate set of equations was devised. Namely, for these structures, a system of columns and slabs were used to estimate the effects of design. In this case, the effects of single-or multiple-story structures were assessed to incorporate not only the effects of concrete strength and reinforcement ratio, but also the effects of increased deadloads with a greater number of stories. These influences were incorporated into this analysis through a method posited by Schmidt et al. [39]. In this work, the contributions of varying foundation and roofing materials were excluded from analysis, but they could lead to notable effects for large structures. The effects on building height and weight on lateral design in seismic regions were also not considered or discussed in this work.
To address concrete strength, reinforcement ratio, and the influence of whether buildings were built with multiple stories or a single story, several inputs were used. These included: • A repeating building unit was used that consisted of 1 slab and 4 columns supporting it.
• The range of compressive strength for concrete considered was between 20 -40 MPa • The steel properties were the same as those for the reinforced concrete members discussed in Section S.3.2. • The environmental impact for concrete as a function of its strength were based on the equations discussed in Section S.3.1. When no mineral additives were used, the parameters for the limestone mixtures at a 0% mineral additive replacement of OPC ratio were used. (Note: while the parameters for all mixtures with a 0% mineral additive replacement ratio had similar parameters, because some inputs used fits, the parameters are not identical. The use of the parameters based on the mixtures with 0% limestone were used as limestone is one of the most prevalent mineral additives used globally [5]). • 20.3% mineral additive content in the cementitious materials based on the global average in 2015 [5] • Water content, = 185 kg/m 3 • Force = (2370 kg/m 3 )(20m × 7m × 0.14m)/4 = 116 kN, assumed applied axial load from concrete slab self-weight for each column; the weight of columns themselves was neglected.
This work determined the role of design inputs for the concrete columns and the required column area, considering single vs multiple story units for varying compressive strength. To do this, again, a standard column height, l, of 3.5 m was consistently applied. The required column cross-section area was defined S14 based on: Where minimum reinforcement ratio, 14+ = 0.01, is assumed when designing according to ACI-318. N is the ratio between the Young's modulus for steel and concrete, equal to E s /E c , and E s is the modulus of steel, which is set here as 207 GPa; E c is the modulus of concrete, which is calculated here as 4700> ′ ! , 22N , and 5000> ′ ! for ACI-318, EC2 and the Indian Standard, respectively. Also, Aconcrete is the cross-sectional area of the concrete column, F is the applied force, and f'c is the compressive strength of the concrete. The total concrete area required for n single story (i.e., unstacked) units, Atotal,unstacked, was given as: Then, the total concrete area required for n stacked units (i.e., multi-story with S being the number of stories) is given by: where Atotal,unstacked, is the total concrete area for the columns in the stacked building. Cumulatively, the environmental impact for either the single-or multi-story units can be written as: respectively.
To capture the influence of the slab in the repeating unit, the slab volume for varying compressive strength was defined using a similar structure as discussed previously. Here, again, a simply supported, one-way flat slab was assumed. It was modeled as having a constant length, l, of 7 m and a constant width, b, of 20 m. The concrete cover was modeled as 0.040 m. To reflect design requirements, constraints were checked in accordance with ACI 318 design code [40]. The required reinforcement ratio, , for varying compressive strength was defined as:

S15
The requisite slab thickness, h, to meet allowable deflection was then specified as: Note: this deflection criterion is for ACI 318, for Eurocode2 the criterion for slab thickness limit for deflection control is l/20 < d < l/14 (where d is the effective depth, not the slab thickness), and for IS slab thickness limit for deflection control is l/20 < d.
Using these relationships, the area of reinforcing steel As, was then written as: The external moment on the slab, Mn, was defined based on the loading and boundary conditions as: Using these parameters, the effective slab depth, d, was then written as: Values for the slab depth were then checked against the requirement and reinforcement ratio limits according to ACI-318. Namely, it was confirmed that the design met the following: The environmental impact for the slab for varying compressive strength was calculated using equation 16.
With these inputs, the total environmental impact for the multi-storey units, Itotal,stacked, and for the singlestory units, Itotal,unstacked, for varying compressive strength were then defined as: respectively.

S16
For Eurocode 2 and Indian Standard, the same equations were used to calculate the required column area but with different minimum reinforcement ratio. Namely, for Eurocode 2, the minimum reinforcement ratio was taken as per equation 19; for the Indian Standard, the minimum reinforcement ratio was taken as 0.008.
For the slab, again some differences were present for the Eurocode 2 and the Indian Standard relative to the above equations based on the ACI code. Namely, for the slab, the following minimum reinforcement ratios were used based on the Eurocode 2: 90.26 !31 ) , 0.0013: (56) and the Indian Standard: Additionally, the required slab depth was calculated using equation 28 (Eurocode 2) and equation 39 (Indian Standard).

S.4. GHG Mitigation from Durability and Use of SCMs
The design life of concrete structures is largely governed by their durability. Current design codes are largely deficient in their ability to quantify design life in relation to the dominant deterioration mechanisms, since they rely on prescriptive rather than performance principles [41]. Codes also often conflate durability with concrete compressive strength, using strength as a proxy for durability. Research has shown that this premise is false [42]; durability is more related to the transport properties (penetrability) of concrete than to its strength, and with a range of SCMs now available, their different chemical performance can be used to advantage even when they display similar compressive strength.
Deterioration due to steel corrosion is the dominant mode of reinforced concrete deterioration. Provided that the various phases can be understood and scientifically described, design life can be quantified and controlled mechanistically, including within a probabilistic framework. Extending the service life of a concrete structure through proper durability design is possible with current knowledge. Other than corrosion of the reinforcing steel, other forms of deterioration exist which can be damaging, such as alkali-aggregate reaction. However, for corrosion, environmental chlorides (e.g., from marine salts or from the de-icing salts) are usually the most aggressive and pernicious problem. Carbonation of the concrete cover can also induce steel corrosion, but this is less pronounced than chlorides; here, a common misconception is that carbonated structures inevitably corrode, but other corrosion-inducing factors of moisture and oxygen must also be present, and frequently, provided the cover to steel is adequate, corrosion does not ensue [43]. Also, the majority of concrete in a building is indoors and protected from the weather and corrosive agents, and many facades are also protected. S17

S.5.1. Historical cement and cement-based material production and longevity
In order to address both GHG emissions from the historical global production of cement and cementbased composites, as well as the effects of increasing concrete in-use longevity, several existing models were implemented concurrently. First, global cement production data, by country or locality, were collected from the United States Geological Survey (USGS), capturing production from 1931-2015 (data from ). To examine in-use stocks, which were used to understand the effects of elongating concrete use-phase life period, the model derived by Cao et al. [71] was implemented. This implementation involved using that model's split ratios between residential, non-residential buildings and infrastructure, as well as in-service lifetimes for concrete structures. Import and export data necessary to convert production data from the USGS to consumption data needed to use by Cao et al.'s model were from the United Nations Comtrade database [72].
The GHG emissions to produce cement and concrete historically were adapted from the calculations presented in Section S.2, which reflect production in 2015. To capture historic cement production, these models were extended to reflect 1990, 1995, 2000, 2005, and 2010 production statistics. Namely, the global demand for different SCMs as well as the electricity required to produce cement and kiln efficiency in each of those years were based on [5]. The fraction of fossil fuels, waste fuels, and biomass used for thermal energy in the cement kilns were from [5]. However, due to limitations in available data, to increase data granularity beyond those general fuel categories, the relative fraction of different fuels within those groups (e.g., coal versus oil in the fossil fuels used) were all based on the relative fractions used in the same reference year, 2018, reported by Global Cement and Concrete Association [6]. The electricity mix for each of these years was based on global data from the International Energy Agency [7].
To extend these calculations to capture concrete production, several additional calculations were performed. The energy demand for other constituents and processes were based on values reported in Section S.2 and the energy grids were based on data from the representative year, using the same grids as were applied for cement production. To capture concrete constituents required, distributions of varying constituent inputs were fit to the data presented in Supplementary [73][74][75][76]. Because these fractions were only reported for some countries/regions, a global fraction of concrete consumption by strength class was estimated by using a weighted fraction by national production statistics reported by the USGS (using data from the representative years, collected as discussed above). The ERMCO reports were also used to collect data on the relative fraction of cement used in concrete, with the exception of data for China, which were based on [77]. While cement produced, but not used in concrete, could be used in several applications, this remaining cement was modeled herein as mortar (using an assumption applied in prior publications [71,77,78]). The distributions of constituents required for mortar production were based on the relative fractions of cement, masonry cement, lime, sand, and water used in the American Standards for Testing Materials (ASTM) protocol [79]. Fractions of mineral additives were based on two factors. The first incorporated the relative quantity of limestone and other fillers reported for masonry cement by the Portland Cement Association (PCA) [80]. All masonry cement modeled based on the ASTM code was assumed to have the same average mineral filler reported by the PCA. In addition to this quantity mineral additive, the second input to mineral additives was that all cement was assumed to have the same general ratio of SCMs as reported above, based on global averages for the years reported.

S.5.2. Historical cement-based material production emissions
To capture full historical emissions profiles for cement and concrete, values were extrapolated from the reference years assessed. Namely, linear interpolation of emissions profiles was applied to years that fell between 1990,1995,2000,2005,2010 and 2015. For all years prior to 1990, emissions were modeled as having the same emissions per kg of cement consumed as was modeled in 1990.
To apply these emissions profiles to other models used in this work, the kg GHG emissions / m 3 concrete (!GHG emissions) was used. This emissions per cubic meter of cement-based material reflects a global average. To apply this factor to historical global cement production, first the mass of cement produced globally was summed annually from the individual nations reported by the USGS (discussed above). Using the distributions for constituents used in cement and concrete discussed in Section S.

S.5.3. GHG emissions reductions as from changes in longevity
The influence of changing cement in-service lifetime to contribute to a potential reduction in cement demand was based on Miller [81]. This potential reduction in cement demand was calculated by using a normal distribution: where " is the mean and # is the standard deviation, based on the modeling assumption by Cao et al. [71]. In this work, the influence that elongating time to removal from in-service life was addressed. S19

S.6. Cumulative GHG emissions reduction potential
To quantitatively assess the reduction in GHG emissions for cement-based materials production possible from each of the strategies considered in this work, several steps of analysis were performed. To determine the annual reduction in GHG emissions per m 3 of concrete between 2015 and 2100, linear interpolation was used between the baseline value in 2015 and the greatest reduction to be achieved in 2100.

S.6.1. Projection of future cement demand
The estimated future cement demand was based on the model developed by Cao et al. [82], which work focused on production after 1950. For this 150-year period, cement inflow was captured based on a stock-driven approach. In this approach, the Gompertz combined model was applied, using the same input parameters as outlined by Cao et al. [82]: where E,3 " is the per capita cement stock at year + , E,(53 is the per capita cement stock saturation; E,3 # is the per capita stock level at the initial time 7 ; j is the sectoral fraction; and A and B refer to parameters that reflect growth patterns over time. The model was used to calculate the growth curve of future per capita cement stock based on in-service lifetimes and stock patterns developed by Cao et al. [82]. Namely, the data for saturation level (medium), saturation times (moderate) and lifetimes were based directly on Cao et al. [82]. Projected population data from the UN World Population Prospects [83] were used to capture anticipated changes in population; the medium variant was used in the analysis herein, and the low and high variants were used to analyze the impact of alternative population growth patterns between 2020-2100 [83]. The ten countries/regions modeled were: (1) North America; (2) Latin America; (3) Europe; (4) Commonwealth of Independent States (CIS); (5) China; (6) India; (7) Africa; (8) the Middle East; (9) Developed Asia & Oceania; and (10) Developing Asia. Cement demand was calculated based on inflow for each application (namely, residential, non-residential, and civil infrastructure -abbreviated as civil herein) for each of the countries/regions noted. To perform this calculation, the following equation was used: where IN E,3 " is the inflow of cement (cement demand) and NET E,3 " is the net-inflow of cement each year, (1 − ( + )) is the survival function, and ( + ) is the normal cumulative distribution function at year + . The standard deviation for the normal distribution is set as 0.2 of the mean lifetimes.
The net-inflow of cement each year is calculated as the difference between the total cement stock in year + and the total cement stock the previous year:

S20
where, 3 " is the population at year + and E,3 " the in-use cement stock per capita.

S.6.2. GHG emissions reduction from altering production processes
The first mitigation method considered was to draw comparisons between improvements that could be implemented in the processes used for cement and concrete production. The efficacy of these improvements was examined through the mean between the three compressive strengths, which was then used to examine emissions reduction potential for year 2100. For the diagrams made in the main article, the reduction achieved if combining all of above production reduction methods was used (see Table S.4). This reduction of GHG emissions to be 79% of the baseline emissions was modeled as being achieved in the year 2100, with a linear interpolation between technology adoption between 2015 and 2100. Reductions are determined between the median GHG emissions of the baseline case and the process-related mitigation methods.

S.6.3. GHG emissions reduction from altering constituents
In addition to altering manufacturing processes, the role of changing constituents used, namely to increase mineral additive content, was considered as a means to reduce GHG emissions from global cement-based materials production. In order to estimate the role these mineral additives could play in lowering GHG emissions, cement replacement levels had to be approximated.
To calculate the potential reduction in environmental impact per m 3 of concrete (as well as mortar used) when using a higher ratio of cement replacement, concrete mixtures were modeled as containing a higher cement replacement ratio than the 2015 baseline (20.3%). To do this, two permutations of increased replacement were considered: one with additional pozzolanic materials (an increase up to 30% SCM content) and one with additional cementitious and pozzolanic materials (an increase up to 50% SCM content). In both of these cases, because a variety of SCMs could be used and new SCM permutations are continuously being researched [84], our models assume the environmental impacts of producing these SCMs to reach higher replacement levels were equivalent to those for quarrying/crushing natural pozzolans.
The GHG emissions reduction potential from using these higher SCM replacement ratio mixtures were compared to the 2015 average GHG emissions per m 3 of concrete (~266 kg CO2-eq/m 3 ) with 20.3% cement replacement on average. A net reduction of 11.1% and 34.0% was estimated for replacement with 30% and 50% SCM replacement, respectively. As such, to determine the annual reduction in GHG emissions per m 3 of concrete between 2015 and 2100, linear interpolation between the baseline value in 2015 and potential target value, 66.0% of projected GHG emissions when higher cement replacement is used was employed.

S.6.4. The role of concrete member design
To incorporate the effects of member design on potential reduction in GHG emissions, the effects of using higher compressive strength in concrete columns for buildings was examined, as well as the effect of optimizing the reinforcement ratio and strength of slabs. This component of buildings was assessed due to the anticipated universality of findings. To determine the volume of concrete that could be reduced through use of higher compressive strength in columns of multi-story buildings, an estimated ratio of concrete used for columns relative to the slab was calculated. To perform this calculation, a 20 story RC structure consisting of four columns and a slab was assumed. Due to varying load on the columns (because the bottom columns are subjected to higher load than the top story columns for example), the average column volume was applied. For the slab, the volume of concrete required when specifying a low compressive strength (20MPa) was used for all design comparisons. Using these inputs, the resulting column-to-slab ratio is 12.0% column and 88.0% slab. The potential saving in concrete volume, and therefore GHG emissions, that can be achieved by optimizing the concrete compressive strength and reinforcement ratio (40MPa with minimum reinforcement), compared to baseline chosen as 30MPa with median reinforcement ratio (3.5%), is 24.3%, 24.1% and 20.7% for the Indian Standard, Eurocode 2 and ACI codes, respectively. In this case, a reduction in GHG emissions for reinforced concrete columns by 2100 was estimated using the following equation (using the average reduction of the design codes): 80.1% * GHG * 12.0% column ratio = 9.6% GHG Similarly, to determine the amount of concrete (or GHG emissions) that could be saved by more efficient design of reinforced concrete slabs, a slab with median reinforcement ratio (0.25%, note that all slabs are deflection controlled and within allowable h/l ratio, resulting in low reinforcement ratio) was assumed as the baseline to compare with the combination of reinforcement ratio and compressive strength that results in the smallest environmental impact for a 1m strip of a reinforced concrete slab. A comparison was made between the three design codes to determine which code generates the smallest impact for a slab with the same span length, subjected to the same load. (In this case, we compared the baseline and lowest impact for ultimate design stage). The reduction in GHG emissions for the slab for the Indian Standard, Eurocode 2 and ACI were 25.2%, 24.4% and 20.9%. The total reduction, on average, in GHG emissions for reinforced concrete slabs by 2100 was estimated as: 76.5% * GHG * 88.0% slab ratio = 67.3% GHG Therefore, the reduction by year 2100 by design optimization of reinforced concrete columns and slabs was estimated to: of the baseline emissions. Note that this only applies to 80% of the total emissions from concrete used for building structural applications (~18% reduction of the total global emissions from cement-based materials), as it was assumed that 20% of concrete is used for other applications than columns and slabs.

S.6.5. The role of elongating concrete service life
To examine the influence of elongating concrete service life, if elongating service life could be used to offset new cement-based materials production, three scenarios were considered. Namely, herein we consider the effects of: 1. The "ideal" scenario -here, all countries/regions of the world are modeled as being able to use up to 50% SCM replacement of Portland cement, and that increase in SCM use could lead to a potential service life extension of up to 4-fold for Res, NonRes and CE. Further, this extension of service life is applied to historic (before 2015) concrete structures, based on the assumption that improvements to cementitious binders have been growing over time. 2. The "realistic" scenario -here, it is assumed that certain parts of the world may not have easy access to SCMs, which could limit the abilities to achieve 50% Portland cement replacement uniformly. As such, it is assumed that only 50% of the world would have access to enough SCMs to meet this replacement ratio, and it is further assumed that only CE structures can reach 4-fold service life extension with buildings (both Res and NonRes) achieving a 3-fold service life extension. Again, here this extension of service life is applied to historic (before 2015) concrete structures, based on the assumption that improvements to cementitious binders have been growing over time. 3. The "future" scenario -here, the assumptions from the "realistic" scenario were considered as only applicable for future concrete structures (i.e., after 2015) and no elongated service life beyond historic trends could be expected for any in-use cement-based materials.
In this counterfactual model, the assumption is made that if structures can last for a longer period of time, it could offset the production of more cement to establish structures of similar purpose. Here, it is found that percent reduced cement demand from elongating service life would be large in regions with shorter service-periods (see Tables S.5 -S.7). As was done with the other mitigation methods, the influence of an increase in concrete longevity on reducing cement demand, and the associated GHG emissions from new material production, linear interpolation between 2015 baseline value and reduction due to in-service life increase as per the 'future' scenario described below. The reduction in cement demand estimated for 2100 was 47.1%, corresponding to 52.9% of materials required relative to if no modifications had been made (up to 4-fold lifetime increase, see Table S.7 for the estimated total reduction for the World). If including the reduced cement demand due to higher use of SCMs (50%) to achieve the increased service-life, the reduction in cement demand estimated for 2100 was 65%.
For the 3 scenarios modeled: -1. Ideal Scenario: SCMs are available so that 50% cement replacement can be achieved all over the world, and the service-lifetime of buildings (Res and NonRes) and Civil can as a result be extended by 4-fold. Lifetime extension has been applied to historic and future concrete structures (built between 1931-2100) -For the ideal scenario, 285.9 Gt cement can be reduced, which is equivalent to 242.0 Gt GHG (55.8% reduction) emissions. -2. Future Only Scenario: SCMs are available so that 50% cement replacement can be achieved all over the world, but the service life is only extended for concrete structures built after 2015.
The service-lifetime of buildings (Res and NonRes) can be extended by 3-fold and infrastructure (CE) can be extended by 4-fold. -For the future scenario, 202.8 Gt cement can be reduced, which is equivalent to 175.7 Gt emissions (47.1% reduction). -For future scenario, but with 30% replacement, the service-life of buildings (Res and NonRes) can be extended by 2-fold and infrastructure (Civile) can be extended by 3-fold. For this scenario, 167.4 Gt cement can be reduced, which is equivalent to 145.1 Gt emissions (38.9% reduction).

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-3. Realistic Scenario: Due to limited accessibility to SCMs in some countries/regions, we assume that 50% cement replacement can be achieved for 50% of all concrete structures built after 2015, and the service-lifetime of buildings (Res and NonRes) can be extended by 3-fold and infrastructure (Civil) can be extended by 4-fold. -For the realistic scenario, 106.4 Gt cement can be reduced, which is equivalent to 92.2 Gt emissions (24.7% reduction).
The results from the sensitivity analysis, where the impact of lower and higher population growth was examined, are shown in Table S.8.

S.6.6. The potential influence of building height
While not a direct part of the GHG emissions mitigation strategies addressed in this work, it has been posited that building height could be a strong influencer on the environmental impacts of the materials selected for the structural design (note: contributions from varying foundations, roofs, and other materials beyond the frame are excluded from consideration) [85]. To conduct an initial examination into the role building height could play in reducing GHG emissions from concrete structures, the effects of stacked versus unstacked units were examined herein (see Section S.3.3).
Using each of the three building codes applied in this work, namely the ACI code, the Eurocode 2, and the Indian Standard, approximate shifts in GHG emissions to produce stacked versus non-stacked structures were estimated. The GHG emissions trends are shown in Figures S1-S3.   The figures above show that designing buildings to be shorter (stacking fewer units, thus having fewer building stories) has the potential to be beneficial in reducing GHG emissions. This result is due less load on concrete columns, and therefore less volume of concrete required to sustain the loads. However, there are limited data on the average building height (globally or for certain countries/regions). Thus, it is difficult to scale these results in order to estimate the mitigation of GHG emissions if shorter buildings than average would be built in the future (or at least not taller since we are likely heading in that direction). Further, these models to do not incorporate factors such as the amount of material needed for roofs, foundations, or other aspects that would vary based on "stacking" structural units versus